Neo4j stores data in nodes connected by directed, typed relationships with properties on both, also known as a Property Graph. It is a high performance graph store with all the features expected of a mature and robust database, like a friendly query language and ACID transactions. | It is a scalable graph database optimized for storing and querying graphs containing hundreds of billions of vertices and edges distributed across a multi-machine cluster. It is a transactional database that can support thousands of concurrent users executing complex graph traversals in real time. |
intuitive, using a graph model for data representation;reliable, with full ACID transactions;durable and fast, using a custom disk-based, native storage engine;massively scalable, up to several billion nodes/relationships/properties;highly-available, when distributed across multiple machines;expressive, with a powerful, human readable graph query language;fast, with a powerful traversal framework for high-speed graph queries;embeddable, with a few small jars;simple, accessible by a convenient REST interface or an object-oriented Java API | Elastic and linear scalability for a growing data and user base;
Data distribution and replication for performance and fault tolerance;
Multi-datacenter high availability and hot backups;
Support for ACID and eventual consistency;
Support for various storage backends: HBase, Cassandra, Bigtable, DynamoDB, BerkeleyDB;
Support for global graph data analytics, reporting, and ETL through integration with big data platforms: Spark, Giraph, Hadoop;
Support for geo, numeric range, and full-text search via:
ElasticSearch, Solr, Lucene;
Native integration with the Apache TinkerPop graph stack;
Open source under the Apache 2 license |
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